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- Introduction: applications, computational models for vision, perception and prior knowledge, levels of vision, how humans see - Pixels and filters: digital cameras, image representations, noise, filters, edge detection - Regions of images and segmentation: segmentation, perceptual grouping, Gestalt theory, segmentation approaches, image compression - Feature detection: RANSAC, Hough transform, Harris corner detector - Object recognition: challenges, template matching, histograms, machine learning - Convolutional neural networks: neural networks, loss functions and optimization, backpropagation, convolutions and pooling, hyperparameters, AutoML, efficient training, selected architectures - Image sequence processing: motion, tracking image sequences, Kalman filter, correspondence problem, optical flow
模块指南汽车软件工程
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